Establishment of topological clustering method by linguistic rules
| Project/Area Number |
17K00332
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Soft computing
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| Research Institution | University of Tsukuba |
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Principal Investigator |
Endo Yasunori 筑波大学, システム情報系, 教授 (10267396)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | クラスタリング / 機械学習 / 持続性ホモロジー / 言語ルール / ファジィ推論 / パーシステントホモロジー / 位相的データ解析 |
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| Outline of Final Research Achievements |
In this research project, we developed a topological language-based clustering technique that can flexibly grasp the structure of data by converting the concept of persistent homology, which plays a central role in topological data analysis, into language-based clustering and incorporating it into language-based clustering. Furthermore, we aimed at the theoretical development of topological language-based clustering and its practical application to mining social data by examining the mathematical relationships between conventional clustering techniques and development techniques.
We have obtained some results on the development of language-based clustering algorithms and clustering algorithms that incorporate persistent homology. Further study on making linguistic rules for persistent homology is a future topic.
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| Academic Significance and Societal Importance of the Research Achievements |
言語ベースのクラスタリングを開発するためには、ソフトコンピューティング技法が欠かせない。本研究課題はそれらの理論を持続性ホモロジーという位相的データ解析の新概念を橋梁として人間の持つ知識と結びつけ、柔軟に処理する手法を開発するだけではなく、さらに俯瞰的立場、すなわち言語ベースという新たな地点に立った位相的データ解析手法の礎となることをゴールとしているものであり、本研究課題の成果によって、データ構造と人間の推論を巧みに組み入れた柔軟なデータ解析手法の深化が期待される。
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Report
(4 results)
Research Products
(31 results)
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[Presentation] Even-sized Clustering with Noise Clustering method2018
Author(s)
Kei Kitajima, Yasunori Endo
Organizer
Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018
Related Report
Int'l Joint Research
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